Microsoft Azure Machine Learning – A Data Tool for the Masses

When I was a freshmen at North Dakota State University in the fall of 1991, I worked as advertising manager at the college newspaper. It was a simple job, motivate the sales reps to sell as many ads as possible so that the editors can publish a big newspaper. Sounds simple doesn’t it? Of course, the size of the newspaper was always decided a few hours before we went to press and being able to predict the size was a difficult task since the only tools we had were Lotus 1-2-3. This decision was always made last minute with all of the data we had available. Times and technology were ripe for disruptive change in 1991!

Fast forward to 2014.

A lot has changed in my life since 1991. But what hasn’t changed is my desire to use information to make good decisions. The only difference is that we have compelling tools and technology to make decisions faster, more accurately and quite possibly much sooner than was ever possible. For years, industries like finance, insurance and retail have had access to these prediction tools and the IT infrastructure to operate them. A very expensive proposition in the past. Today, that game has changed. There are many lower cost options a business or individual can use to do the things the big boys have been doing for years. We’ve watched the rise of predicative open source tools like “R” and self-service tools like PowerPivot, Tableau and Qlik become pervasive in many small and midmarket organizations. The promise of faster adhoc analysis and the ability to predict with easy to use tools are here now.

Enter Azure Machine Learning.

In July of this year, Microsoft made a major announcement in the predicative analytics space. The pre-release/beta announcement of Microsoft Azure Machine Learning was upon us. I’ve been dabbling in open source “R” for the past year and many times have become frustrated with my lack of skill in the details of predictive modeling using a command line interface. That confidence and frustration was completely eliminated once I started building models with Microsoft Azure Machine Learning.

Operational Predictive Analytics Made Easy.

Microsoft Azure Machine Learning makes it easy to build experiments with a learning curve less steep than pure “R.” The tool’s success is going to come from making predictive models operational in a much shorter amount of time and at a lower cost. Can you say ROI? Microsoft has been committed to predictive analytics for many releases of SQL Server and while the tools work, making the results and usage of those models operational was a substantial customized undertaking. Microsoft Azure Machine Learning changes this by automating the deployment of proven experiment models to web services that can seamlessly be integrated with web applications and visualization tools.

How Can I Learn More?

On September 25th the Business Intelligence Chicagoland meetup group will be discussing and reviewing our work with Microsoft Azure Machine Learning. We’ll start with a demonstration of how to build a model and integrate with a website and then we’ll transition to a customer retention case study we’ve been working on and look at how the service can be utilized to solve real world business problems. I hope you can join us!

To learn more about Business Intelligence Solutions, please join us for our next complimentary Chicagoland Business Intelligence event where Rachael Narel will dispel the myths around today’s miracle BI cures and spell out a realistic, pragmatic approach to accomplishing the robust executive dashboard your CEO is looking for.